CN-121994407-A - Method for calibrating signals of soil pressure optical fiber sensor

CN121994407ACN 121994407 ACN121994407 ACN 121994407ACN-121994407-A

Abstract

The invention relates to a signal calibration method of an earth pressure optical fiber sensor, which comprises the steps of optical fiber setting and data acquisition, multi-factor aging glue layer life prediction model construction, glue layer residual life and shearing strength degradation function calculation, segment-glue layer-optical fiber strain transfer model and theoretical strain transfer coefficient calculation, optical fiber signal long-term drift compensation model construction, IOT intelligent demodulation and actual measurement strain transfer coefficient calculation, optical fiber health index construction, optical fiber signal transmission calibration based on health indexes, optical fiber signal precision judgment and calibration result output. The method has the advantage that the aging and signal attenuation mechanisms of the optical fiber sensor under the complex working conditions of temperature and humidity circulation, soil pressure, load change and the like are analyzed by introducing a multi-factor aging and adhesive layer degradation model. By means of dynamic calibration and drift compensation, the problem that the accuracy of an existing optical fiber monitoring system is gradually degraded in the long-term service process is solved, and the long-term stability of optical fiber signals is improved.

Inventors

ZHENG ZHITAO
SHEN WENBING
LI SHAOHUA
LI CHUANG
GUAN JUNMING
ZHANG WEN
WEI ZONGCHENG
WANG ZHENGYANG

Assignees

中国建筑第五工程局有限公司

Dates

Publication Date: 20260508
Application Date: 20260310

Claims (10)

1. The method for calibrating the signal of the soil pressure optical fiber sensor is characterized by comprising the following steps of: S1, setting optical fibers and collecting data, wherein the optical fibers comprise optical fiber sensor component layout, working condition data collection, optical fiber IOT collection node construction and data uploading; s2, constructing a multi-factor aging glue layer life prediction model, namely calculating the theoretical total life of the glue layer ; S3, calculating residual service life and shear strength degradation function of the adhesive layer, wherein the calculation comprises the calculation of residual service life of the adhesive layer and the construction of the shear strength degradation function of the adhesive layer; S4, calculating a segment-glue layer-optical fiber strain transfer model and a theoretical strain transfer coefficient, wherein the segment-glue layer-optical fiber strain transfer model comprises the steps of constructing a basic strain transfer relationship and calculating the theoretical strain transfer coefficient; s5, building an optical fiber signal long-term drift compensation model, intelligent IOT demodulation and actual measurement strain transfer coefficient calculation, wherein the method comprises the steps of building the drift compensation model, intelligent cloud signal demodulation of the Internet of things and actual measurement strain transfer coefficient calculation; s6, constructing optical fiber health indexes, wherein the construction comprises glue layer service life judgment, transmission coefficient calculation and optical fiber health index calculation; S7, optical fiber signal transmission calibration based on health indexes comprises basic calibration coefficient calculation, dynamic calibration factors combined with the health indexes calculation and strain and stress calculation after calibration; s8, outputting the accuracy judgment and calibration result of the optical fiber signals according to the health index Judging the signal precision and outputting the calibration result 。
2. The method for calibrating the signal of the soil pressure optical fiber sensor according to claim 1, wherein the specific method in the step S1 comprises the steps of arranging optical fiber sensor components and collecting working condition data, embedding the optical fiber soil pressure sensor in a duct piece structure, and measuring axial strain And hoop strain Arranging soil pressure boxes on four sides of the duct piece for collecting soil pressure data And collecting the temperature T (T), the humidity RH (T) and the jacking load L (T) of the surrounding environment of the duct piece through an environment sensor.
3. The method for calibrating the soil pressure optical fiber sensor signals is characterized in that the specific method in the step S1 further comprises the steps of constructing and uploading data by an optical fiber IOT acquisition node, wherein each optical fiber sensing unit is connected with an Internet of things node, the Internet of things node comprises an optical fiber demodulation module, a microprocessor, a wireless communication module and a local cache unit, and the acquired strain, temperature and humidity and working condition parameter data are uploaded to a cloud in real time through the wireless communication module.
4. The method for calibrating the signal of the soil pressure optical fiber sensor according to claim 1, wherein the specific method in the step S2 is that an improved Eyring type multi-factor aging life model is adopted, and factors such as temperature, humidity, load, temperature and humidity circulation and the like are comprehensively considered, so that the theoretical total life of the adhesive layer is calculated: In the middle of In order for the time to fail, As a function of the theoretical degradation time constant, Is the apparent activation energy of the aging of the adhesive layer, Is a boltzmann constant, Is the absolute temperature of the environment in which the glue layer is located, As the coefficient of the acceleration of the humidity, In order to be of a relative humidity level, As the acceleration coefficient of the load, As a result of the load factor, For the initial shear strength or initial shear load capacity of the adhesive layer, Is the temperature and humidity circulation acceleration coefficient, Is an index of equivalent temperature and humidity cycle times or cycle strength; is the working shear stress born by the adhesive layer in the actual service state, To characterize the amount of degradation of "the shear strength decays from an initial value to an operating stress level".
5. The method for calibrating a signal of an optical fiber sensor for soil pressure according to claim 4, wherein the specific method of step S3 is ① for calculating the remaining life of the adhesive layer by using a formula Calculating the accumulated service time of the sensor and reusing the formula Calculating theoretical residual life of adhesive layer, and constructing ② adhesive layer shearing strength degradation function by using formula Constructing a model of the shear strength degradation of the adhesive layer Indicating the time of installation of the sensor, Indicating the current time of the monitoring, Indicating the cumulative length of service of the sensor, The theoretical residual life of the adhesive layer is represented, The shear strength of the adhesive layer when the service time is t, Indicating the initial shear strength of the glue line, Representing a dimensionless degradation function.
6. The method for calibrating a soil pressure optical fiber sensor signal according to claim 5, wherein the specific method of step S4 is ① strain transfer basic relationship construction by using a formula Defining strain transfer coefficient, ② calculating theoretical strain transfer coefficient by simplifying structure-adhesive layer-optical fiber into serial or shearing hysteresis system formed from segment structural rigidity, adhesive layer shearing rigidity and optical fiber self-rigidity, and utilizing theoretical analysis or finite element fitting to obtain theoretical strain transfer coefficient In the middle of Is the true strain of the segment of the pipe, The strain is measured for the optical fiber, In order to be a coefficient of strain transfer, As a function of the theoretical strain transfer coefficient, For the initial strain transfer coefficient, Is an empirical index.
7. The method for calibrating a signal of an optical fiber sensor for soil pressure according to claim 4, wherein the specific method of step S5 comprises ① drift compensation model building, performing accelerated aging test on the sensor in a laboratory, and performing constant stress test Under the condition, the drift of the output strain of the optical fiber along with time is recorded: And fine compensation correction is carried out on the same: ② cloud intelligent signal demodulation of the Internet of things, namely a cloud server receives the Internet of things data from the step S1, performs time alignment and data integrity check, multidirectional Bragg grating FBG, temperature and historical stress data fusion on each sensing node, wherein Indicating a constant stress, the stress is constant, Indicating the drift amount of the output strain of the recording optical fiber with time, t is the accumulation time, Representing the original output of the optical fiber, Representing the strain after drift compensation.
8. The method for calibrating a soil pressure optical fiber sensor signal according to claim 7, wherein the specific method of step S5 further comprises the step of actually measuring strain transfer coefficients, namely obtaining segment reference strain through a structural analysis or a comparison sensor in a selected calibration time window Strain measured after drift compensation of optical fiber Then calculate the actual strain transfer coefficient Where j represents the j-th calibration sample point, N represents the total number of samples, For the reference strain of the jth sensor position, For the measured strain after compensation for the jth position, Indicating the measured strain transfer coefficient.
9. The method for calibrating a signal of an optical fiber sensor for soil pressure according to claim 8, wherein the specific method in step S6 is that ① is used for judging the service life of the adhesive layer, and the ratio of the service life of the adhesive layer is defined as follows: When (1) , When (1) , ② Transfer coefficient accuracy ratio calculation, defining transfer coefficient ratio: ; The actual measurement transfer efficiency is basically consistent with the theoretical prediction; the actual measurement strain of the optical fiber is smaller than the theoretical strain value, and the result is smaller; The measured transmission efficiency is better than the theoretical estimation, ③ the calculation of the optical fiber health index, namely, comprehensively considering the residual life and the transmission coefficient deviation, and defining the optical fiber health index: when (when) The optical fiber-glue layer system is healthy and does not need to be calibrated when The health degree of the optical fiber is degraded, and the calibration is needed when Indicating that the fiber channel is scrapped and removed from the monitoring system The service life ratio of the adhesive layer is shown, And the transmission coefficient ratio is represented, and H represents the optical fiber health index.
10. The method for calibrating a signal of an optical fiber sensor for soil pressure according to claim 8, wherein the specific method of step S7 is that ① basic calibration coefficients are calculated by first constructing calibration coefficients based on strain transfer coefficients: when (when) In the time-course of which the first and second contact surfaces, Indicating that the optical fiber measurement needs to be amplified when In the time-course of which the first and second contact surfaces, The method comprises the steps of reducing optical fiber measured values, calculating dynamic calibration factors combined with health indexes by ②, and constructing comprehensive calibration factors: And ③ strain and stress after calibration, namely optical fiber strain after drift compensation The method comprises the following steps of: according to the constitutive relation of the materials or the structural analysis model, the calibrated strain is converted into the stress response of the subway segment: In the middle of Represents a calibration factor based on the strain transfer factor, As a monotonic function that can be fitted by empirical formulas or machine learning models, Indicating the calibration of the fiber strain after drift compensation, For the equivalent modulus of elasticity, the elastic modulus, Representing the stress response of the subway pipe.

Description

Method for calibrating signals of soil pressure optical fiber sensor Technical Field The invention belongs to the field of structural health monitoring, and relates to a signal calibration method of an earth pressure optical fiber sensor. Background The optical fiber sensing technology has wide application in structural health monitoring (Structural Health Monitoring, SHM), especially in long-term monitoring of large-span structures, tunnels, subway segments and other infrastructures, and optical fiber sensing is an important technical means for structural monitoring due to the advantages of corrosion resistance, electromagnetic interference resistance, high spatial resolution and the like. Particularly, the distributed optical fiber sensing (Distributed Fiber Optic Sensing, DFOS) system can provide high-precision and long-time span real-time monitoring, and is widely applied to the fields of concrete structures, soil structures and the like. Currently, there are many studies and patent technologies about optical fiber strain sensors. For example, patent document publication No. CN110162860a proposes extrapolating the life of an optical fiber system by a temperature acceleration test, as an evaluation index of degradation of system performance based on the relative attenuation percentage of temperature change. However, the technology has the defect that the accelerated aging factor is too single, only the temperature is considered as the accelerated factor, and the performance degradation of the optical fiber strain sensing system under the environment changes such as humidity change, soil pressure fluctuation, temperature and humidity circulation and the like under the actual complex working condition is ignored. In addition, the method adopts a black box strategy, extrapolates the service life through empirical fitting, and does not deeply analyze the influence of a key interface (such as the bonding performance between a glue layer and an optical fiber) on the system performance, so that the physical mechanism of the method lacks definition, and multiple degradation factors possibly encountered by the optical fiber in the long-term service process cannot be accurately simulated. In addition, patent document with publication number CN101713691a proposes application of a distributed optical fiber strain sensor in health monitoring of tunnel structure, and stress and deformation of the tunnel segment are monitored by arranging the optical fiber strain sensor in the tunnel segment. The system effectively improves the spatial resolution and the global coverage capacity of tunnel monitoring. However, the system still cannot fully consider the changes of the optical fiber sensor along with time, humidity, corrosion, soil pressure and other complex environmental conditions in long-term monitoring, and how to dynamically calibrate the sensor accuracy in an actual engineering environment. In the prior art, an effective compensation and correction mechanism is lacked for an aging mechanism, signal drift and precision degradation of an optical fiber sensor, so that the sensor can have signal transmission efficiency reduction and precision loss in a long-term service period, and the reliability of monitoring data is reduced. In addition, patent document with publication number CN116792155A proposes a tunnel health state monitoring and early warning method based on distributed optical fiber sensing, and multi-parameter data fusion and analysis are adopted, so that real-time monitoring and overrun early warning in a certain range can be realized. However, the method mainly relies on a preset stress threshold value to carry out overrun alarm, and does not consider the precision change of the optical fiber sensor in long-term service. Fiber optic monitoring systems typically assume that their performance remains unchanged throughout the life cycle, but in practice, the sensitivity, signal transfer efficiency, and strain transfer characteristics of fiber optic sensors change over time and with changes in environmental conditions. The prior art fails to provide a systematic solution for dynamically calibrating and correcting these degradation factors. In summary, although the prior art has made an important contribution in optical fiber strain sensing and distributed optical fiber monitoring, there are significant drawbacks in various practical applications, particularly in environments where underground structures are monitored for a long period of time. The long-term stability and precision degradation of the optical fiber sensor under various complex working conditions cannot be fully considered in the prior art, an effective dynamic calibration and long-term health assessment mechanism is lacked, and the requirements of a modern urban underground structure on long-term accurate monitoring and life cycle management cannot be met. Disclosure of Invention The invention aims to solve the problems of aging, drifting, signal